几种CUDA加速高斯滤波算法的比较

Comparation of several CUDA accelerated Gaussian filtering algorithms

目前已有几种CUDA加速的图像高斯滤波算法,但这些算法有的描述不清楚,也没有人对它们的性能进行详尽的比较,这给理解及应用带来了困难。描述了几种CUDA加速的图像高斯滤波算法,包括直观的实现方式、使用共享内存的分离滤波器方法、使用纹理内存的分离滤波器方法、基于CUFFT的卷积滤波以及递归高斯滤波器。强调了这些算法的核心思想,比较了它们的时间复杂度,通过实验对它们的性能进行了分析。

There are some image filtering algorithms based on CUDA, but some of them are not clearly described, and no one to compare the performance of these algorithms, which brings difficulties for understanding and using these algorithms. This paper discusses five different Gaussian image filters based on CUDA, they are naive method, separable share memory method, separa- ble texture memory method, FFT convolution filtering and recursive Gaussian filter. Core ideas are emphasized, time complexi- ties are compared, and performances are analyzed through experiments.